We talked about what investors are looking for when they are assessing an AI company for investment, and how important the AI piece is to the overall investment thesis. There was a clear consensus that a lot of companies are re-skinning themselves as AI companies to appear more cutting-edge and interesting, because they have built some AI features or automation into an application, as opposed to being genuinely AI-native in their approach. Investors are trying to look beyond this and taking a more discerning approach to companies that claim to be AI-driven; looking to understand what problem is being solved and how and whether AI really drives a competitive advantage.

AI is the next generation of software

The conversation then moved on to which industries and applications have the greatest potential for AI. We examined whether AI is in fact a valid investment theme, or whether it is just that the next generation of software, in whatever application, will need to be AI-driven. The panel agreed that AI is going to be ubiquitous, that all software will need to be intelligent, and just as people rarely say they invest in SaaS these days, pretty soon no-one will be talking about investing in AI as a sector.

Scaling is hard

As with any start-up founded by highly technical founders, there comes a point where hard conversations need to be had about the right leadership for the company in order for it to scale and commercialise. This is not unique to AI companies, but the investors commented that it can be particularly hard to persuade deep tech experts to accept and respect a CEO who does not have the same level of technical understanding as themselves.

Higher valuations are justified

The investors were generally fairly sanguine about the fact that AI companies are highly valued. They pointed to the scarcity of genuinely AI-native companies with world-leading talent, and also to the fact that if we accept the thesis that the next generation of software will be AI-driven, then the leaders in this field should command a premium over “ordinary” SaaS in the same way that SaaS commands a premium over legacy on-premise software.

Ethics have (some) place in investor decision-making

There was also a discussion around the role that investors could or should have in considering ethics when making investment decisions in AI companies. There was clear agreement that there is collective responsibility to avoid obviously unsavoury propositions, but less clarity around the social implications. The example we discussed was backing a company that uses AI to analyse images for medical purposes. To what extent should the AI algorithm be making decisions on what is or is not worthy of a follow-up? What happens if there is a mistake? Who is responsible? By and large, the investors felt that these sorts of issues were not for them to decide.